Bio


Prof. Alonso is the founder and director of the Aerospace Design Laboratory (ADL) where he specializes in the development of high-fidelity computational design methodologies to enable the creation of realizable and efficient aerospace systems. Prof. Alonso’s research involves a large number of different manned and unmanned applications including transonic, supersonic, and hypersonic aircraft, helicopters, turbomachinery, and launch and re-entry vehicles. He is the author of over 200 technical publications on the topics of computational aircraft and spacecraft design, multi-disciplinary optimization, fundamental numerical methods, and high-performance parallel computing. Prof. Alonso is keenly interested in the development of an advanced curriculum for the training of future engineers and scientists and has participated actively in course-development activities in both the Aeronautics & Astronautics Department (particularly in the development of coursework for aircraft design, sustainable aviation, and UAS design and operation) and for the Institute for Computational and Mathematical Engineering (ICME) at Stanford University. He was a member of the team that currently holds the world speed record for human powered vehicles over water. A student team led by Prof. Alonso also holds the altitude record for an unmanned electric vehicle under 5 lbs of mass.

Academic Appointments


  • Professor, Aeronautics and Astronautics

Administrative Appointments


  • Member, SoE Future Committee (2015 - 2016)
  • Director, NASA Fundamental Aeronautics Program Office (2006 - 2008)

Honors & Awards


  • AIAA SciTech Best Paper Award, Thermophysics Technical Committee, AIAA (2014)
  • NASA Aeronautics Associate Administrator Award for High-Fidelity Tool Validation for Sonic Boom, NASA (2014)
  • AIAA Associate Fellow, AIAA (2012)
  • FAI Altitude World Record, Class U, Unmanned Aerial Vehicles, Electric category, FAI (2010)
  • NASA Exceptional Public Service Medal, NASA (2009)
  • AIAA Best Paper Award, Multi-Disciplinary Optimization Conferences, AIAA (2004, 2006, 2008)

Boards, Advisory Committees, Professional Organizations


  • Member, NASA Advisory Council (2005 - 2006)
  • Member, Sec. of Transp. Future of Aviation Advisory Council (2010 - 2011)
  • Member, FAA Management Advisory Council (2011 - 2014)
  • Member, FAA Drone Advisory Council (2016 - Present)

Professional Education


  • PhD, Princeton University, Mechanical & Aerospace Engineering (1997)
  • M.A., Princeton University, Mechanical & Aerospace Engineering (1993)
  • B.S., Massachusetts Institute of Technology, Aeronautics & Astronautics (1991)

Patents


  • Juan J. Alonso, Andre S. Chan, Ferdinand Hendriks. "United States Patent 7,177,116 System, Method, and Apparatus for Breaking Up Large-Scale Eddies and Straightening Air Flow Inside Rotary Disk Storage Devices", Sep 1, 2005
  • Juan J. Alonso, Andre S. Chan, Ferdinand Hendriks. "United States Patent 7,946,691 System, Method, and Apparatus for Applying Boundary Layer Manipulation Techniques to the Air Flow Inside Rotary Disk Storage Devices", Sep 1, 2005

All Publications


  • Performance optimizations for scalable implicit RANS calculations with SU2 COMPUTERS & FLUIDS Economon, T. D., Mudigere, D., Bansal, G., Heinecke, A., Palacios, F., Park, J., Smelyanskiy, M., Alonso, J. J., Dubey, P. 2016; 129: 146-158
  • SU2: An Open-Source Suite for Multiphysics Simulation and Design AIAA JOURNAL Economon, T. D., Palacios, F., Copeland, S. R., Lukaczyk, T. W., Alonso, J. J. 2016; 54 (3): 828-846

    View details for DOI 10.2514/1.J053813

    View details for Web of Science ID 000375425800004

  • Unsteady Continuous Adjoint Approach for Aerodynamic Design on Dynamic Meshes AIAA JOURNAL Economon, T. D., Palacios, F., Alonso, J. J. 2015; 53 (9): 2437-2453

    View details for DOI 10.2514/1.J053763

    View details for Web of Science ID 000359983400002

  • Enabling the environmentally clean air transportation of the future: a vision of computational fluid dynamics in 2030 PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES Slotnick, J. P., Khodadoust, A., Alonso, J. J., Darmofal, D. L., Gropp, W. D., Lurie, E. A., Mavriplis, D. J., Venkatakrishnan, V. 2014; 372 (2022)
  • Enabling the environmentally clean air transportation of the future: a vision of computational fluid dynamics in 2030. Philosophical transactions. Series A, Mathematical, physical, and engineering sciences Slotnick, J. P., Khodadoust, A., Alonso, J. J., Darmofal, D. L., Gropp, W. D., Lurie, E. A., Mavriplis, D. J., Venkatakrishnan, V. 2014; 372 (2022)

    Abstract

    As global air travel expands rapidly to meet demand generated by economic growth, it is essential to continue to improve the efficiency of air transportation to reduce its carbon emissions and address concerns about climate change. Future transports must be 'cleaner' and designed to include technologies that will continue to lower engine emissions and reduce community noise. The use of computational fluid dynamics (CFD) will be critical to enable the design of these new concepts. In general, the ability to simulate aerodynamic and reactive flows using CFD has progressed rapidly during the past several decades and has fundamentally changed the aerospace design process. Advanced simulation capabilities not only enable reductions in ground-based and flight-testing requirements, but also provide added physical insight, and enable superior designs at reduced cost and risk. In spite of considerable success, reliable use of CFD has remained confined to a small region of the operating envelope due, in part, to the inability of current methods to reliably predict turbulent, separated flows. Fortunately, the advent of much more powerful computing platforms provides an opportunity to overcome a number of these challenges. This paper summarizes the findings and recommendations from a recent NASA-funded study that provides a vision for CFD in the year 2030, including an assessment of critical technology gaps and needed development, and identifies the key CFD technology advancements that will enable the design and development of much cleaner aircraft in the future.

    View details for DOI 10.1098/rsta.2013.0317

    View details for PubMedID 25024413

    View details for PubMedCentralID PMC4095895

  • PDE-constrained optimization with error estimation and control JOURNAL OF COMPUTATIONAL PHYSICS Hicken, J. E., Alonso, J. J. 2014; 263: 136-150
  • Helicopter Rotor Design Using a Time-Spectral and Adjoint-Based Method JOURNAL OF AIRCRAFT Choi, S., Lee, K., Potsdam, M. M., Alonso, J. J. 2014; 51 (2): 412-423

    View details for DOI 10.2514/1.C031975

    View details for Web of Science ID 000333798200006

  • Using Supervised Learning to Improve Monte Carlo Integral Estimation AIAA JOURNAL Tracey, B., Wolpert, D., Alonso, J. J. 2013; 51 (8): 2015-2023

    View details for DOI 10.2514/1.J051655

    View details for Web of Science ID 000322557400019

  • Robust Grid Adaptation for Efficient Uncertainty Quantification AIAA JOURNAL Palacios, F., Duraisamy, K., Alonso, J. J., Zuazua, E. 2012; 50 (7): 1538-1546

    View details for DOI 10.2514/1.J051379

    View details for Web of Science ID 000306096400009

  • Risk Assessment of Scramjet Unstart Using Adjoint-Based Sampling Methods AIAA JOURNAL Wang, Q., Duraisamy, K., Alonso, J. J., Iaccarino, G. 2012; 50 (3): 581-592

    View details for DOI 10.2514/1.J051264

    View details for Web of Science ID 000301204700007

  • Multidisciplinary Optimization with Applications to Sonic-Boom Minimization ANNUAL REVIEW OF FLUID MECHANICS, VOL 44 Alonso, J. J., Colonno, M. R. 2012; 44: 505-526
  • Prediction of Helicopter Rotor Loads Using Time-Spectral Computational Fluid Dynamics and an Exact Fluid-Structure Interface JOURNAL OF THE AMERICAN HELICOPTER SOCIETY Choi, S., Datta, A., Alonso, J. J. 2011; 56 (4)
  • Design of Adjoint-Based Laws for Wing Flutter Control JOURNAL OF AIRCRAFT Palaniappan, K., Sahu, P., Jameson, A., Alonso, J. J. 2011; 48 (1): 331-335

    View details for DOI 10.2514/1.C031005

    View details for Web of Science ID 000287227200031

  • Toward optimally seeded airflow on hypersonic vehicles using control theory COMPUTERS & FLUIDS Marta, A. C., Alonso, J. J. 2010; 39 (9): 1562-1574
  • Numerical and Mesh Resolution Requirements for Accurate Sonic Boom Prediction AIAA 42nd Aerospace Sciences Meeting and Exhibit Choi, S., Alonso, J. J., van der Weide, E. AMER INST AERONAUT ASTRONAUT. 2009: 1126–39

    View details for DOI 10.2514/1.34367

    View details for Web of Science ID 000268906100005

  • Two-Level Multifidelity Design Optimization Studies for Supersonic Jets AIAA 43rd Aerospace Sciences Meeting and Exhibit Choi, S., Alonso, J. J., Kroo, I. M. AMER INST AERONAUT ASTRONAUT. 2009: 776–90

    View details for DOI 10.2514/1.34362

    View details for Web of Science ID 000266894200005

  • Aircraft design optimization 6th Pan-American Workshop on Applied and Computational Mathematics Alonso, J. J., LeGrestey, P., Pereyra, V. ELSEVIER SCIENCE BV. 2009: 1948–58
  • ADJoint: An approach for the rapid development of discrete adjoint solvers AIAA/ISSMO 11th Multidisciplinary Analysis and Optimization Conference Mader, C. A., Martins, J. R., Alonso, J. J., van der Weide, E. AMER INST AERONAUT ASTRONAUT. 2008: 863–73

    View details for DOI 10.2514/1.29123

    View details for Web of Science ID 000254658300006

  • Multifidelity design optimization of low-boom supersonic sets AIAA/ISSMO 10th Multidisciplinary Analysis and Optimization Conference Choi, S., Alonso, J. J., Kroo, I. M., Wintzer, M. AMER INST AERONAUT ASTRONAUT. 2008: 106–18

    View details for DOI 10.2514/1.28948

    View details for Web of Science ID 000252820400013

  • A methodology for the development of discrete adjoint solvers using automatic differentiation tools INTERNATIONAL JOURNAL OF COMPUTATIONAL FLUID DYNAMICS Marta, A. C., Mader, C. A., Martins, J. R., van der Weide, E., Alonso, J. J. 2007; 21 (9-10): 307-327
  • Integrated computations of an entire jet engine 52nd ASME Turbo Expo 2007 Medic, G., You, D., Kalitzin, G., Herrmann, M., Ham, F., Pitsch, H., van der Weide, E., Alonso, J. AMER SOC MECHANICAL ENGINEERS. 2007: 1841–1847
  • Demonstration of nonlinear frequency domain methods AIAA JOURNAL McMullen, M., Jameson, A., Alonso, J. 2006; 44 (7): 1428-1435

    View details for DOI 10.2514/1.15127

    View details for Web of Science ID 000239046300006

  • An adjoint method for the calculation of remote sensitivities in supersonic flow INTERNATIONAL JOURNAL OF COMPUTATIONAL FLUID DYNAMICS Nadarajah, S. K., Jameson, A., Alonso, J. 2006; 20 (2): 61-74
  • Unsteady CFD simulation of an entire gas turbine high-spool 51st ASME Turbo Expo 2006 Schuelter, J., Apte, S., Kalitzin, G., Pitsch, H., van der Weide, E., Alonso, J. AMER SOC MECHANICAL ENGINEERS. 2006: 1931–1939
  • A framework for coupling Reynolds-averaged with large-eddy simulations for gas turbine applications JOURNAL OF FLUIDS ENGINEERING-TRANSACTIONS OF THE ASME Schluter, J. U., Wu, X., Kim, S., Shankaran, S., Alonso, J. J., Pitsch, H. 2005; 127 (4): 806-815

    View details for DOI 10.1115/1.1994877

    View details for Web of Science ID 000231839800021

  • A coupled-adjoint sensitivity analysis method for high-fidelity aero-structural design OPTIMIZATION AND ENGINEERING Martins, J. R., Alonso, J. J., Reuther, J. J. 2005; 6 (1): 33-62
  • Integrated simulations of a compressor/combustor assembly of a gas turbine engine 50th ASME Turbo-Expo 2005 Schluter, J., Wu, X., Pitsch, H., Kim, S., Alonso, J. AMER SOC MECHANICAL ENGINEERS. 2005: 971–982
  • Prediction of high-pressure turbine main-/secondary-air system flow interaction JOURNAL OF PROPULSION AND POWER Davis, R. L., Alonso, J. J., Yao, J. X., Paolillo, R., SHARMA, O. P. 2005; 21 (1): 158-166
  • Multi-element high-lift configuration design optimization using viscous continuous adjoint method JOURNAL OF AIRCRAFT Kim, S., Alonso, J. J., Jameson, A. 2004; 41 (5): 1082-1097
  • High-fidelity aerostructural design optimization of a supersonic business jet AIAA/ASME/ASCE/AHS/ASC/SDM 43rd Structures, Structural Dynamics, and Materials Conference Martins, J. R., Alonso, J. J., Reuther, J. J. AMER INST AERONAUT ASTRONAUT. 2004: 523–30
  • The complex-step derivative approximation ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE Martins, J. R., Sturdza, P., Alonso, J. J. 2003; 29 (3): 245-262
  • Massively parallel simulation of the unsteady flow in an axial turbine stage JOURNAL OF PROPULSION AND POWER Yao, J. X., Davis, R. L., Alonso, J. J., Jameson, A. 2002; 18 (2): 465-471
  • Development and validation of a massively parallel flow solver for turbomachinery flows JOURNAL OF PROPULSION AND POWER Yao, J. X., Jameson, A., Alonso, J. J., Liu, F. 2001; 17 (3): 659-668
  • Perspectives on simulation based aerodynamic design 1st International Conference on Computational Fluid Dynamics (ICCFD) Jameson, A., Martinelli, L., Alonso, J., Vassberg, J., Reuther, J. SPRINGER-VERLAG BERLIN. 2001: 135–178
  • Simulation based aerodynamic design 2000 IEEE Aerospace Conference Jameson, A., Martinelli, L., Alonso, J. J., Vassberg, J. C., Reuther, J. I E E E. 2000: 55–87
  • Aerodynamic shape optimization of supersonic aircraft configurations via an adjoint formulation on distributed memory parallel computers COMPUTERS & FLUIDS Reuther, J., Alonso, J. J., Rimlinger, M. J., Jameson, A. 1999; 28 (4-5): 675-700
  • Constrained multipoint aerodynamic shape optimization using an adjoint formulation and parallel computers, part 2 JOURNAL OF AIRCRAFT Reuther, J. J., Jameson, A., Alonso, J. J., Rimlinger, M. J., Saunders, D. 1999; 36 (1): 61-74
  • Constrained multipoint aerodynamic shape optimization using an adjoint formulation and parallel computers, part 1 JOURNAL OF AIRCRAFT Reuther, J. J., Jameson, A., Alonso, J. J., Rimlinger, M. J., Saunders, D. 1999; 36 (1): 51-60